Learning professionals are increasingly looking to bring learning analytics to the centre of business leaders. But to do so effectively they have to be clear-eyed about the challenges of communicating an evidence-based narrative about learning to time-poor executive stakeholders.
Effective communication about learning data should start with understanding the organizational context within which those data will be received and acted upon. The wider arena of business analytics.
With L&D heads reporting that leadership wants a data-driven approach from them and learning analytics moving to the front and center of the new L&D skillset, it becomes really important to answer this question: how should you, as a learning professional, talk to the business about data?
Perhaps the best starting point for working out how you can offer value to the business through your engagement with learning analytics is to start by looking at things from the point of view of your internal customers. What does the business actually want and need from you?
To begin with, let’s be clear about what we mean by learning analytics in this context.
What is learning analytics?
Learning analytics can be defined as the measurement, collection, analysis and reporting of data about learning activities. There is much more to using data than just reporting what happened with learning activities in the past. It can also lead to predictive and prescriptive analytics, which make more active uses of data to predict what will happen in the future and to map out learning paths. But generally, when people talk about learning analytics, they are looking to find out what happened with a given intervention and why it happened.
What does the business want from learning analytics?
In order to understand where learning analytics ‘fits’ in the organizational context, it helps to have a clear-cut view of how businesses use their operating data; the management information (MI) that gets reported on at meetings where decisions are made.
The rhythm might vary in different organizations according to scale, ownership, geographical spread, seasonality and other factors, but generally, businesses live tax year to tax year, quarter to quarter, and most have some kind of monthly reporting round. The higher up the tree you go, the more data-driven the meetings are where these reports get reacted to and discussed.
Some of this data is business-critical (and therefore often confidential). Some data are of less pressing interest. Generally, the more business-critical, confidential and threat- or opportunity-laden the data are, the more interesting they look to business leaders. Financials generally come first priority, followed often by sales. In most businesses, sales are underpinned by marketing. HR has data on churn and other people metrics, a subset of which may be training data. And so on. There’s a pecking order of time and attention.
Given the large amount of data available, and the pressures on business leaders’ time, presentation has to be brief and relevant. The principal occasions on which data really gets drilled into is when there is an outlier, an exceptional result, either good or bad. We’ve had a massive uptick in sales in one territory: why did it happen? What are we doing right? Or … we’re getting cancelled on social media: why did that happen? What are we doing wrong?
Efficiently run businesses don’t lurch from crisis to crisis. But even the best-run organizations can get blindsided and have to react to unforeseen circumstances (e.g. the Covid-19 pandemic). They often have long-term, macro changes in the external environment they are coping with, such as climate change or the decline of physical retail traffic, which will tick along slowly in the background for years, then suddenly through some unexpected event blow up and rapidly accelerate in significance.
4 tips for making learning data part of business analytics
Given these pressures, businesses aren’t, generally speaking, that interested in things that happened two months ago (ie the impact evaluation of your training program). What they want to know badly are things like, ‘are we going to make our number this year-end / this quarter / this month?’, along with, ‘how can we make sure that happens?’, and ‘how can we stop the bad thing happening that might get us all humiliated/fired/sued?’.
It is against this background that we have to contextualize the frequent calls for L&D, through the use of data, to talk to the business about things the business cares about. The following reflections on this injunction flow from the paragraphs above.
- Things the business cares about is a moving target. What the business needs to know about in any given year, quarter or month will change with the situation it finds itself in and the new priorities shaped by events often out of its control.
- Information about the past is only of compelling interest to the extent that it can help the business grapple with critical issues it faces right now and for the future.
- The business doesn’t want to see your workings out. If you only measure outcomes you might know that learning succeeded, but not why it succeeded (or didn’t). But while it is really important for you, as a learning professional, to have working metrics that examine every critical stage of the process, the business may only be interested in final outcomes: for example, ROI, a measurable change in performance or behaviour, and even a reduction in risk.
- There are dangers in relying too heavily on dashboard data. Dashboard data is static and inert in character. It tells us about the present, but nothing about the future or what we should do about it.
Leadership teams are always looking to identify levers that can change some aspect of the business. This could be to reduce attrition, to mitigate risk or improve overall performance. If L&D are in a position to provide evidence of a lever to the top table, leaders will be compelled to use it. And so, the consensus view seems to be that L&D needs to improve and safeguard its position within the organization by using data analytics. But in order to do that it has to be proactive on data in a way that, so far as the majority of organizations are concerned, nobody in the business is asking for or expecting. L&D has to overcome the risks that this move might bring, of exposing its own knowledge gaps, or of uncovering bad results that nobody wants to hear about.
But the potential upsides of making this move are huge; greater control over its own destiny, a place at the top table, and the chance to play a decisive role in responding to the imperative that business schools, analysts and consultants have been urging on organizations for years – to create a learning organization that is flexibly and appropriately skilled to meet the challenges of the modern volatile, uncertain and constantly disrupted business environment.
Download our new eBook, ‘Adding data and learning analytics to your organization’ to find out more.
Ben serves as CEO for Learning Pool. Previously, Ben served as Chief Product Officer for Learning Pool where he worked to help define and develop Learning Pool’s next generation of workplace digital learning platforms, with a focus on Learning Experience Platforms and the Learning Analytics space.
Before Learning Pool, Ben helped to build HT2 Labs from humble beginnings into a globally recognized innovator in workplace digital learning. Learning Pool completed an acquisition of HT2 Labs in June 2019.
Ben’s expertise is based in research, having previously completed his PhD researching the impact of gamification on adult social learning, Ben has authored and contributed chapters for many books, has two peer-reviewed academic papers and has presented at conferences around the world, including TEDx.